The Intention to Leave: An Overview of the Factors Determining the Turnover from the Teaching Career in the Romanian Education System

Bianca Andreea Hurjui ()
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Bianca Andreea Hurjui: PhD student - Școala Națională de Studii Politice și Administrative, Teach for Romania

Enformation Conference Proceedings Series, 2024, vol. 14, 139-157

Abstract: To maintain a high level of education quality, schools must attract new and well-prepared teachers while retaining and developing existing and effective ones (Guarino, Santibanez, and Daley, 2006). In this context, the issue of teacher retention becomes an increasingly intense concern, especially since the teaching profession is extremely demanding, generating stress, burnout, and potentially leading to the intention to leave the system (Farber B., 2000). Exhausted, some teachers choose to leave their careers in the early years of activity, others in the middle of their careers, or when they have reached the final stage of professional development. Although working conditions are similar, teachers’ responses to stress and its consequences are relatively different (Chang, 2009). Thus, this study investigates the predictors of the intention to leave, considering the career development stage of Romanian teachers. The study is presented as a comparative analysis, and its main contribution is the understanding of specific factors leading to the turnover from the profession at different career points. The research method used is a sociological survey based on a questionnaire. A total of 194 teachers from the Romanian pre-university education system responded online to a questionnaire that addresses their work experience, including aspects such as working conditions, mindset towards stress, receptivity to distress, degree of emotional exhaustion, depersonalization, and reduced personal accomplishment, as well as the intention to leave.The data is analyzed using the SPSS program, employing multiple regression analysis to test the effects of each predictor on the intention to leave, depending on the career development stage. The data is analyzed using the SPSS program, employing multiple regression analysis to test the effects of each predictor on the intention to leave, depending on the career development stage.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:enf:proc24:art9:v:14

DOI: 10.63467/alls14.art9

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